Author: Rick Dunkelberger
WTI Business Applications Meteorologist

In advance of next week’s USDA crop reduction report (12 Aug, 08:30 EST), I chose to illustrate a statistically effective model (from G. Considine, Aquilla Energy) for forecasting monthly average corn farm prices received in Illinois, for the time period starting in April and ending in December. As with most commodities weather is an increasingly important aspect to take into account when trying to predict price changes associated with supply and demand. The number of cooling degree days which are typically associated as units used to relate the day’s temperature to energy demands, can also be used to measure the accumulation of heat within a month. As with corn, temperature is an import contributor to seasonal yield amounts, furthermore to the daily fluctuation in corn prices.

By inputting a time series trend, July CDDs, August CDDs, April opening price ($/bu), one is able to account for a statistically significant portion (R^2 = 0.7) of corn price changes throughout the period spanning April to December.

For this December we are forecasting an Illinois December corn price to come in somewhere around $3.05-$3.10/bu. This would be a 22% decrease from April’s corn price which was valuated at $3.81/bu. The model does not take into account economic variables, and is thus solely weather driven. The importance of this commentary is to demonstrate the value of information one can receive from an accurate weather forecast.

This entry was posted on Tuesday, August 4th, 2009 at 8:13 am and is filed under Agriculture, Global Commodities, Grains, United States, weather. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.